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About MDAnalysis |
The MDAnalysis Community is interested in all facets of working with data in the computational molecular sciences. We welcome everyone. We all follow our [Code of Conduct] and strive to create an environment that is welcoming to all. Our primary purpose is to produce software that scientists in academia and industry will trust to use in their research.
We develop and maintain projects related to the broader goal of processing and analyzing data in the computational molecular sciences. We aim to empower users/developers to work with our packages following [FAIR principles]. Our central package is the [MDAnalysis library] for the analysis of computer simulations of many-body systems at the molecular scale.
We believe that scientific software should be open to all while using best practices to maintain high standards of correctness and reproducibility. We emphasize educating our users to make best use of the tools that we produce, to enable them to become contributors to our community and code bases.
MDAnalysis is developed and maintained as a freely available, open-source project by a global community of scientists. The MDAnalysis community adheres to our Code of Conduct and invites everyone to participate --- be it on GitHub Discussions, through issue reports, or code contributions.
All contributors to the MDAnalysis library and its subprojects are acknowledged
in a file called AUTHORS
in each source code repository and in the list of
contributions; as examples see the AUTHORS
file for
mdanalysis
and the contributors for
MDAnalysis/mdanalysis.
MDAnalysis and the algorithms implemented in the library and the subprojects are scientific software that are described in academic publications.
MDAnalysis is used in a variety of other molecular dynamics tools.
All our code and our teaching materials are available under open source licenses from repositories at https://github.com/MDAnalysis/. The MDAnalysis library itself is published under the GNU General Public License, version 2; other supporting libraries are published under the MIT or the BSD-3 clause licence.
Installable packages are available through the popular pip
and
conda
package managers as well as some Linux distributions.
Project leadership is provided by a subset of contributors, the MDAnalysis Core Developers (@MDAnalysis/coredevs) who have produced substantial contributions over extended lengths of time and who remain active in reviewing issues and discussions on GitHub Discussions and our Discord server.
The Core Developers lead the MDAnalysis project and are responsible to the community and to NumFOCUS, our fiscal sponsor. They represent the project publicly and vote to make decisions for the project.
PIs on a grant submitted by MDAnalysis via NumFOCUS must be Core Developers while co-PIs do not have to be Core Developers.
Core Developers are granted commit rights (write access) to the [GitHub source code repositories][orgrepo] and thus can approve pull requests for merges.
The current @MDAnalysis/coredevs team ("MDAnalysis Core Developers") consists of:
- @fiona-naughton
- @hmacdope
- @IAlibay
- @jennaswa
- @lilyminium
- @micaela-matta
- @orbeckst
- @richardjgowers
- @RMeli
- @tylerjereddy
- @yuxuanzhuang
Emerita/Emeritus Core Developers are former Core Developers who remain connected to the project but have stepped back from the day-to-day decision making. Emeriti Core Developers can reinstate themselves to Core Developer status.
Emeriti Core Developers maintain commit rights (write access) to the [GitHub source code repositories][orgrepo] and can approve pull requests for merges.
The current Emeriti Core Developers are:
- @dotsdl
- Elizabeth Denning
- @jandom
- @jbarnoud
- @kain88-de
- @mnmelo
- @mtiberti
- @nmichaud
- @PicoCentauri
- @seb-buch
- @zemanj
- All decisions are made by simple majority1 of the MDAnalysis Core Developers.
- New Core Developers are elected with a simple majority of current MDAnalysis Core Developers.
- Current Core Developers are polled annually to opt-in to remain a Core Developer; otherwise they transition to Emerita/Emeritus Core Developer status.
Everyone in the MDAnalysis community adheres to our Code of Conduct. A rotating subset of three MDAnalysis Core Developers is tasked to respond to and to investigate Code of Conduct violations.
MDAnalysis is a fiscally sponsored project of [NumFOCUS][], a nonprofit dedicated to supporting the open source scientific computing community.
If you like MDAnalysis and want to support our mission, please consider making a donation to support our efforts. NumFOCUS is a 501(c)(3) non-profit charity in the United States; as such, donations to NumFOCUS are tax-deductible as allowed by law. As with any donation, you should consult with your personal tax adviser or the IRS about your particular tax situation.
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We are grateful for financial support from the following organizations, which have supported MDAnalysis either through direct funding or indirectly by funding MDAnalysis contributors.
MDAnalysis has been supported by the Essential Open Source for Science (EOSS) program from the CZI Donor-Advised Fund (DAF), an advised fund of Silicon Valley Community Foundation (funder DOI 10.13039/100014989)
- EOSS5, 2022-253062 (2022): MDAnalysis: Outreach and Project Manager (Personnel: @IAlibay, @jennaswa, @micaela-matta, @orbeckst, @richardjgowers (PI))
- EOSS4, DAF2021-237663, DOI https://doi.org/10.37921/426590wiobus (2021): MDAnalysis: Faster, Extensible Molecular Analysis for Reproducible Science (Personnel: @fiona-naughton, @hmacdope, @IAlibay, @ianmkenney, @lilyminium, @orbeckst (PI), @richardjgowers)
The following contributors were sponsored to work on MDAnalysis through the Google Summer of Code program.
- 2024: @ljwoods2, @lunamorrow, @talagayev
- 2023: @marinegor, @xhgchen
- 2022: @aya9aladdin, @BFedder
- 2021: @ojeda-e, @orioncohen
- 2020: @cbouy, @hmacdope, @yuxuanzhuang
- 2019: @NinadBhat
- 2018: @ayushsuhane, @davidercruz
- 2017: @utkbansal
- 2016: @fiona-naughton, @jdetle
The following technical writers were sponsored to work on MDAnalysis through the Google Season of Docs program.
- 2019: @lilyminium
Earlier work was partially supported by the NSF (as part of award ACI-1443054).
- NSF DIBBS award, ACI-1443054 (2014): CIF21 DIBBs: Middleware and High Performance Analytics Libraries for Scalable Data Science (MDAnalysis Personnel: @orbeckst)
The following students were sponsored to work on MDAnalysis through the NSF Research Experience for Undergraduates (REU) program.
- 2021: @ALescoulie, @edisj
- 2020: @edisj
- 2019: @nawtrey
- 2018: @hfmull
- 2017: @kaceyaurum
- 2016: @rbrtdlgd
- 2015: @ianmkenney
MDAnalysis thanks NumFOCUS for its continued support as our fiscal sponsor, as well as through its Small Development Grants (SDG) program.
- SDG Round 2 (2023): Unified and comprehensive documentation and learning resources for MDAnalysis (Personnel: @IAlibay, @jennaswa, @lilyminium, @micaela-matta, @orbeckst)
- SDG Round 2 (2022): Improving the organization and content of MDAnalysis teaching materials (Personnel: @micaela-matta, @pgbarletta)
- SDG Round 1 (2020): Periodic boundary handling and on the fly transformations
- SDG Round 2 (2018): MDAnalysis tutorial and hackathon
- SDG Round 1 (2017): Widening platform availability for MDAnalysis: Full Python 3 Support
The following contributors were sponsored to work on MDAnalysis through the Outreachy program.
- 2024: @adetutudeborah
- 2022: @umak1106
The following contributors were sponsored to work on MDAnalysis through the Station1 Frontiers Fellowship program.
- 2023: @jong9559, @KarenBekhazi
MDAnalysis welcomes feedback for improvement from its users and community. If you have any general feedback or comments to make about MDAnalysis, the community, events, or other aspects, please let us know in this form here!
[Code of Conduct]: {{ site.baseurl }}/pages/conduct/ [MDAnalysis library]: {{ site.github.repo }} [FAIR principles]: https://www.go-fair.org/fair-principles/ [NumFOCUS]: https://www.numfocus.org [simple majority]: https://en.wikipedia.org/wiki/Majority#Majority_vote [orgrepo]: https://github.com/MDAnalysis [Chan Zuckerberg Initiative]: https://chanzuckerberg.com/
Footnotes
-
A [simple majority][] is defined as more than half the votes cast. Abstentions or blanks are excluded in calculating a majority vote. Totals do not include votes cast by someone not entitled to vote2 or improper multiple votes by a single member. Illegal votes3 are counted as votes cast;
if only two choices (such as a binary "yes"/"no" vote) are possible, a majority vote is more "yes" than "no" votes. ↩ -
See MDAnalysis Core Developers for the list of individuals entitled to vote. ↩
-
Illegal votes are votes that were cast for ineligible choices. ↩